Seedream 5.0 Pro está no ar | Experimente no Gerador de Imagens →

AI Fat Filter

wavespeed-ai /

AI Fat Filter transforms a portrait image into a fun, exaggerated fat version. Upload a face photo and get an entertaining result. Ready-to-use REST inference API, no coldstarts, affordable pricing.

image-to-image
Entrada

Ocioso

$0.05por execução·~20 / $1

Próximo:

ExemplosVer todos

Modelos relacionados

README

AI Fat Filter

AI Fat Filter adds a hilarious twist to any portrait — transforming faces into fun, chubby versions that are guaranteed to get laughs. Perfect for pranks, memes, and those "what if" moments. Upload a photo and prepare to giggle.

Why Choose This?

  • Instant transformation See a hilariously exaggerated version of any face in seconds.

  • Realistic yet funny AI creates natural-looking transformations that are amusing without being uncanny.

  • Meme-ready output Results are perfect for sharing, pranking friends, or creating viral content.

  • Works on any face Selfies, group photos, celebrity pics — transform anyone (with their permission, of course).

  • Quick laughs Upload → Transform → Laugh → Share. Simple as that.

Parameters

ParameterRequiredDescription
imageYesPortrait photo to transform (URL or upload)

How to Use

  1. Upload a photo — any clear face photo works.
  2. Run — AI works its magic.
  3. Laugh — enjoy the transformation.
  4. Share — send it to friends (and maybe run).

Pricing

OutputCost
Per image$0.05

Best Use Cases

  • Friend pranks — Send them their "alternate universe" self.
  • Party entertainment — Transform everyone at the party and vote on the funniest.
  • Meme creation — Content gold for social media.
  • Birthday gags — Add to birthday cards for extra laughs.
  • Group chat fun — Guaranteed reactions in any group chat.

Pro Tips

  • Clear, front-facing photos with good lighting work best.
  • Full face visibility = better transformation.
  • Higher resolution photos give funnier, more detailed results.
  • Try it on yourself first before pranking others!
  • Works great with celebrity photos too (for personal entertainment).

Notes

  • Image is the only required field.
  • Ensure uploaded image URLs are publicly accessible.
  • For entertainment purposes only.
  • Please use responsibly — only transform photos of people who would find it funny.
Nota:Este site utiliza modelos de IA fornecidos por terceiros.

Ai Fat Filter API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/ai-fat-filter with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Ai Fat Filter below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/ai-fat-filter" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
  RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
    -H "Authorization: Bearer $WAVESPEED_API_KEY")
  RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/ai-fat-filter";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/wavespeed-ai/ai-fat-filter", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

Ai Fat Filter API — Frequently asked questions

What is the Ai Fat Filter API?

Ai Fat Filter is a WaveSpeedAI model for image editing, exposed as a REST API on WaveSpeedAI. AI Fat Filter transforms a portrait image into a fun, exaggerated fat version. Upload a face photo and get an entertaining result. Ready-to-use REST inference API, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Ai Fat Filter API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/ai-fat-filter.

How much does Ai Fat Filter cost per run?

Ai Fat Filter starts at $0.050 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Ai Fat Filter accept?

Key inputs: `image`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/ai-fat-filter.

How long does Ai Fat Filter take to generate?

Median end-to-end generation time on WaveSpeedAI is around 19 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Ai Fat Filter outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

AI Fat Filter | Fast Image Editing API | WaveSpeedAI